# LTS Distribution Choice

Choosing a long-term-support Linux release so security updates continue for years without forced upgrades.

**Rests on:** Data Ownership and Privacy

**Leads to:** Reverse Proxy and TLS, WSL and VM Setup

*MLOps and Platform · Self-Hosting*


## Why learn this

Choosing an LTS distribution matters because it determines how long your self-hosted services keep receiving security updates without forced upgrades. With an LTS release, you get years of predictable patching — time to focus on running your applications (like those you'll manage with Docker Compose and Portainer) rather than chasing version upgrades. This unlocks the ability to build stable infrastructure for Container Orchestration Basics, Privacy Engineering, and Inference Optimization, because the foundation underneath those systems doesn't suddenly change underneath you.


## The intuition

Think of your operating system as the foundation of a building. If you keep swapping the foundation, everything on top — your Docker containers, your reverse proxy, your VPN — has to be rebuilt or adjusted, and you risk cracks. An LTS (long-term support) release is like choosing a foundation that is guaranteed to stay solid for a set number of years, with scheduled repairs (security patches) but no surprise demolition dates. The trade-off: you don't get the newest fixtures (latest software versions), but you get predictability. In self-hosting, you control everything, so you must also plan for maintenance. An LTS distribution gives you a slow, expected cadence so you can plan upgrades when you choose, not when the operating system forces you.


## An analogy

Imagine you own a small restaurant. You have two options for your supply vendor: one delivers the freshest ingredients daily but changes its menu and pricing every month; another delivers reliable, standard staples with a price lock for five years, but you won't get exotic seasonal items. The first vendor might seem exciting, but every month you have to rework your menu, retrain your staff, and risk running out of a dish because the supplier stopped carrying it. The second vendor gives you stability — you know what you'll have next year, you can build a loyal customer base, and you only have to renegotiate every few years. The trade-off: you miss out on the newest spice that might have made your signature dish better. In self-hosting, the OS is your vendor. An LTS distribution is the reliable vendor: you get security patches (like consistent quality) for years, but you don't get the newest kernel features or software versions that rolling releases offer. This analogy breaks down when you consider that the OS is not a third party — you are both the restaurant owner and the vendor. You control the patching schedule, but if you pick a non-LTS release, you are choosing a vendor that changes monthly, and you must keep up. The point remains: predictability over novelty.


## Definition

Choosing a long-term-support (LTS) Linux distribution means selecting an operating system release that is officially maintained with security and stability updates for a fixed, multi-year period, so you can run your self-hosted services without being forced to upgrade to the next release.


## How it connects

This concept is a foundation for your self-hosting journey. You already have notes on Docker Compose, Reverse Proxy and TLS, Tailscale Mesh Networking, and Backups. Choosing an LTS distribution underpins all of those: it ensures that the host OS stays secure while your containers run, and it gives you a stable platform for Docker and system services. It's part of the 'Secure Infrastructure' branch, leading to 'Privacy Engineering' and 'Inference Optimization'.


## The mathematics

The mathematics here is not calculus or algebra — it's basic arithmetic and simple comparisons. The core operation is counting time. You need to know how many months or years of support you get from a given release, and then compare that to your own planning horizon (e.g., 'I want to not touch the server for 3 years'). With arithmetic, you can subtract the current date from the end-of-life date to know your remaining support window. For example, if a release was made in April 2020 and supported for 5 years, then it will receive updates until April 2025. The 'math' is subtraction and comparison. This choice is not about equations but about understanding a time line.

Remaining support years = EndOfLifeYear - CurrentYear (for releases with month-level precision, include months: remaining_months = (end_year - current_year) * 12 + (end_month - current_month)). Choose the release where remaining support ≥ your planned usage period.


## A worked example

```
Let's say you are setting up a home server in October 2024. You have two options: Ubuntu 22.04 LTS (released April 2022, supported for 5 years until April 2027) and Ubuntu 24.04 LTS (released April 2024, supported until April 2029). You want to run this server for at least 3 years without upgrading the OS.

Step 1: Ubuntu 22.04: 2027 - 2024 = 3 years of support remaining   # If you install 22.04 in 2024, you have about 3 years left before it goes out of support.
Step 2: Ubuntu 24.04: 2029 - 2024 = 5 years of support remaining   # If you install 24.04, you get 5 years, which exceeds your 3-year requirement.
Step 3: Comparison: 5 years (24.04) > 3 years (22.04)   # You need at least 3 years, so 24.04 is the better choice, despite being newer.

Result: Choose Ubuntu 24.04 LTS because it provides 5 years of support, comfortably covering your 3-year plan, without needing an upgrade mid-way.
```


## Common misconceptions

**LTS is always the best choice** — LTS is always the best choice because it has more support years.

LTS trades newest packages for stability. If you need a specific new kernel feature or a newer Python version that isn't available in the LTS repositories, you might end up compiling software or using third-party repositories, which can be more work and even less secure. In fact: LTS is best for long-term stability, but only if the software you need is available for it. If you need cutting-edge tools, you might be better off with a rolling release or by using containers to isolate the newer software.

**LTS means guaranteed updates forever** — Once I choose an LTS, I get security updates forever.

LTS has a finite support period, typically 5 years for Ubuntu LTS, sometimes 10 with ESM. After that, you stop getting security patches, and your server becomes vulnerable. In fact: LTS gives you a predictable but finite window of support. You should schedule an upgrade before the end-of-life date.

**Upgrades happen automatically, so I don't need to plan** — The OS will upgrade itself, so I don't need to worry about upgrades.

LTS releases do not typically upgrade to the next LTS automatically; you have to perform a manual release upgrade, which can involve downtime and configuration changes. In fact: Upgrade planning is still necessary, but it's infrequent (every few years) and can be scheduled during a maintenance window.

**All LTS distributions are the same** — Any LTS distribution will work; I just need 'LTS' in the name.

Different distributions (Ubuntu, Debian, CentOS Stream, etc.) have different support periods, package availability, and community/enterprise support. Ubuntu LTS is very common for AI, but Debian LTS might have older packages. In fact: Choose an LTS that is officially supported by the tooling you plan to use (e.g., many AI libraries specifically test against Ubuntu LTS).


## In short

An LTS distribution is a multi-year commitment to stability and security updates, trading newest packages for predictable patching. The choice hinges on how long you plan to run the server and whether your AI tools officially support that distribution. Remember: check the end-of-life date, compare it to your planned usage period, and prefer what the tooling officially supports.


## Where this is used

In practice, when self-hosting AI tools — such as a local LLM server, a RAG pipeline, or an agent framework — the choice of LTS distribution affects how smoothly you can deploy and maintain the software stack. Many AI frameworks and model serving libraries (like PyTorch, TensorFlow, and vLLM) are tested against specific Ubuntu LTS versions; using an LTS like Ubuntu 22.04 or 24.04 means those libraries will have pre-built binaries and clear support. In large language model deployments, you might use a cloud VM with Ubuntu LTS to host an inference server; the OS's security patches keep the host safe while the model runs. On small devices (e.g., a Raspberry Pi for on-device AI), Debian-based LTS distros are common, and their long support window means you don't have to rebuild the device image frequently. In RAG applications, the embedding and vector database components run as containers on the host; an LTS host reduces the chance of a container breaking due to an OS update. Agentic systems that call tools often rely on a stable runtime environment; an LTS distribution provides that. In everyday applied ML, data scientists often use Ubuntu LTS on their workstations because it balances software availability with stability. A developer will typically run `ssh` into a server, install Docker and then use `docker compose up` to launch services; the OS underneath is just the stable base. If you choose a non-LTS release, the risk is that an OS update changes a library dependency, breaking your container or your Python environment. With LTS, those surprises are minimised. The key practice is to check the official documentation for the AI tool you're using — it will often say 'Tested on Ubuntu 22.04 LTS' — and then select that exact distribution.


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Read this on the web: https://basavapurushottam.com/learn-ai/lts-distribution-choice
